DynamicMovingAveragesLibrary "DynamicMovingAverages"
Custom Dynamic Moving Averages that allow a dynamic calculation beginning from the first bar
SMA(sourceData, maxLength)
Dynamic SMA
Parameters:
sourceData (float)
maxLength (int)
EMA(src, length)
Dynamic EMA
Parameters:
src (float)
length (int)
DEMA(src, length)
Dynamic DEMA
Parameters:
src (float)
length (int)
TEMA(src, length)
Dynamic TEMA
Parameters:
src (float)
length (int)
WMA(src, length)
Dynamic WMA
Parameters:
src (float)
length (int)
HMA(src, length)
Dynamic HMA
Parameters:
src (float)
length (int)
VWMA(src, volsrc, length)
Dynamic VWMA
Parameters:
src (float)
volsrc (float)
length (int)
SMMA(src, length)
Dynamic SMMA
Parameters:
src (float)
length (int)
LSMA(src, length, offset)
Dynamic LSMA
Parameters:
src (float)
length (int)
offset (int)
RMA(src, length)
Dynamic RMA
Parameters:
src (float)
length (int)
ALMA(src, length, offset_sigma, sigma)
Dynamic ALMA
Parameters:
src (float)
length (int)
offset_sigma (float)
sigma (float)
HyperMA(src, length)
Dynamic HyperbolicMA
Parameters:
src (float)
length (int)
Indicators and strategies
WTDMANLevelParserLibrary "WTDMANLevelParser"
Provides a parsing library that indicator authors can use in order to parse WTDMAN Levels.
parseLevels(s)
Parses the string content and returns the `wtdLevels` found within.
Parameters:
s (string) : The string to parse.
Returns: The parsed WTD levels.
zoneRange
Fields:
high (series float)
low (series float)
wtdLevels
Fields:
lvns (array)
lvnZones (array)
supplyLines (array)
supplyZones (array)
vses (array)
vahs (array)
vals (array)
pocs (array)
miscZones (array)
miscLines (array)
fbos (array)
fbds (array)
majorLevels (array)
manLines (array)
manmajLines (array)
BaseLibrary "Base"
n_atr(source, length)
Parameters:
source (float)
length (simple int)
xma(ma_type, source, length)
Parameters:
ma_type (string)
source (float)
length (simple int)
UtilityLibraryLibrary "UtilityLibrary"
A collection of custom utility functions used in my scripts.
milliseconds_per_bar()
Gets the number of milliseconds per bar.
Returns: (int) The number of milliseconds per bar.
realtime()
Checks if the current bar is the actual realtime bar.
Returns: (bool) `true` when the current bar is the actual realtime bar, `false` otherwise.
replay()
Checks if the current bar is the last replay bar.
Returns: (bool) `true` when the current bar is the last replay bar, `false` otherwise.
bar_elapsed()
Checks how much of the current bar has elapsed.
Returns: (float) Between 0 and 1.
even(number)
Checks if a number is even.
Parameters:
number (float) : (float) The number to evaluate.
Returns: (bool) `true` when the number is even, `false` when the number is odd.
sign(number)
Gets the sign of a float.
Parameters:
number (float) : (float) The number to evaluate.
Returns: (int) 1 or -1, unlike math.sign() which returns 0 if the number is 0.
atan2(y, x)
Derives an angle in radians from the XY coordinate.
Parameters:
y (float) : (float) Y coordinate.
x (float) : (float) X coordinate.
Returns: (float) Between -π and π.
clamp(number, min, max)
Ensures a value is between the `min` and `max` thresholds.
Parameters:
number (float) : (float) The number to clamp.
min (float) : (float) The minimum threshold (0 by default).
max (float) : (float) The maximum threshold (1 by default).
Returns: (float) Between `min` and `max`.
remove_gamma(value)
Removes gamma from normalized sRGB channel values.
Parameters:
value (float) : (float) The normalized channel value .
Returns: (float) Channel value with gamma removed.
add_gama(value)
Adds gamma into normalized linear RGB channel values.
Parameters:
value (float) : (float) The normalized channel value .
Returns: (float) Channel value with gamma added.
rgb_to_xyz(Color)
Extracts XYZ-D65 channels from sRGB colors.
Parameters:
Color (color) : (color) The sRGB color to process.
Returns: (float tuple)
xyz_to_rgb(x, y, z)
Converts XYZ-D65 channels to sRGB channels.
Parameters:
x (float) : (float) The X channel value.
y (float) : (float) The Y channel value.
z (float) : (float) The Z channel value.
Returns: (int tuple)
rgb_to_oklab(Color)
Extracts OKLAB-D65 channels from sRGB colors.
Parameters:
Color (color) : (color) The sRGB color to process.
Returns: (float tuple)
oklab_to_rgb(l, a, b)
Converts OKLAB-D65 channels to sRGB channels.
Parameters:
l (float) : (float) The L channel value.
a (float) : (float) The A channel value.
b (float) : (float) The B channel value.
Returns: (int tuple)
rgb_to_oklch(Color)
Extracts OKLCH channels from sRGB colors.
Parameters:
Color (color) : (color) The sRGB color to process.
Returns: (float tuple)
oklch_to_rgb(l, c, h)
Converts OKLCH channels to sRGB channels.
Parameters:
l (float) : (float) The L channel value.
c (float) : (float) The C channel value.
h (float) : (float) The H channel value.
Returns: (float tuple)
hues(l1, h1, l2, h2, dist)
Ensures the hue angles are set correctly for linearly interpolating OKLCH.
Parameters:
l1 (float) : (float) The first L channel value.
h1 (float) : (float) The first H channel value.
l2 (float) : (float) The second L channel value.
h2 (float) : (float) The second H channel value.
dist (string) : (string) The preferred angular distance to use. Options: `min` or `max` (`min` by default).
Returns: (float tuple)
lerp(a, b, t)
Linearly interpolates between two values.
Parameters:
a (float) : (float) The starting point (first value).
b (float) : (float) The ending point (second value).
t (float) : (float) The interpolation factor .
Returns: (float) Between `a` and `b`.
smoothstep(t, precise)
A non-linear (smooth) interpolation between 0 and 1.
Parameters:
t (float) : (float) The interpolation factor .
precise (bool) : (bool) Sets if the calc should be precise or efficient (`true` by default).
Returns: (float) Between 0 and 1.
ease(t, n, v, x1, y1, x2, y2)
A customizable non-linear interpolation between 0 and 1.
Parameters:
t (float) : (float) The interpolation factor .
n (float) : (float) The degree of ease (1 by default).
v (string) : (string) The easing variant type: `in-out`, `in`, or `out` (`in-out` by default).
x1 (float) : (float) Optional X coordinate of starting point (0 by default).
y1 (float) : (float) Optional Y coordinate of starting point (0 by default).
x2 (float) : (float) Optional X coordinate of ending point (1 by default).
y2 (float) : (float) Optional Y coordinate of ending point (1 by default).
Returns: (float) Between 0 and 1.
mix(color1, color2, blend, space, dist)
Linearly interpolates between two colors.
Parameters:
color1 (color) : (color) The first color.
color2 (color) : (color) The second color.
blend (float) : (float) The interpolation factor .
space (string) : (string) The color space to use for interpolating. Options: `rgb`, `oklab`, and `oklch` (`rgb` by default).
dist (string) : (string) The anglular distance to use for the hue change when the color space is set to `oklch`. Options: `min` and `max` (`min` by default).
Returns: (color) Blend of `color1` and `color2`.
VolumeProfileLibrary "VolumeProfile"
Analyzes volume and price and calculates a volume profile, in particular the Point Of Control and Value Area values.
new(rowSizeInTicks, valueAreaCoverage, startTime)
Constructor method that creates a new Volume Profile
Parameters:
rowSizeInTicks (float) : Internal row size (aka resolution) of the volume profile. Useful for most futures contracts would be '1 / syminfo.mintick'. Default '4'.
valueAreaCoverage (int) : Percentage of total volume that is considered the Value Area. Default '70'
startTime (int) : Start time (unix timestamp in milliseconds) of the Volume Profile. Default 'time'.
Returns: VolumeProfile object
method calculatePOC(vp)
Calculates current Point Of Control of the VP
Namespace types: VolumeProfile
Parameters:
vp (VolumeProfile)
Returns: void
method calculateVA(vp)
Calculates current Value Area High and Low of the VP
Namespace types: VolumeProfile
Parameters:
vp (VolumeProfile)
Returns: void
method update(vp, h, l, v, t)
Processes new chart data and sorts volume into rows. Then calls calculatePOC() and calculateVA() to update the VP. Parameters are usually the output of request.security_lower_tf.
Namespace types: VolumeProfile
Parameters:
vp (VolumeProfile)
h (array) : Array of highs
l (array) : Array of lows
v (array) : Array of volumes
t (array) : Array of candle times
Returns: void
method setSessionHigh(vp, h)
Sets the high of the session the VP is tracking
Namespace types: VolumeProfile
Parameters:
vp (VolumeProfile)
h (float)
Returns: void
method setSessionLow(vp, l)
Sets the low of the session the VP is tracking
Namespace types: VolumeProfile
Parameters:
vp (VolumeProfile)
l (float)
Returns: void
method getPOC(vp)
Gets the current Point Of Control
Namespace types: VolumeProfile
Parameters:
vp (VolumeProfile)
Returns: Point Of Control (float)
method getVAH(vp)
Gets the current Value Area High
Namespace types: VolumeProfile
Parameters:
vp (VolumeProfile)
Returns: Value Area High (float)
method getVAL(vp)
Gets the current Value Area Low
Namespace types: VolumeProfile
Parameters:
vp (VolumeProfile)
Returns: Value Area Low (float)
VolumeProfile
Fields:
rowSizeInTicks (series float)
valueAreaCoverage (series int)
startTime (series int)
valueAreaHigh (series float)
pointOfControl (series float)
valueAreaLow (series float)
sessionHigh (series float)
sessionLow (series float)
volumeByRow (map)
totalVolume (series float)
pocRow (series float)
pocVol (series float)
KernelFunctionsRPLibrary "KernelFunctionsRP"
This library provides non-repainting kernel functions for Nadaraya-Watson estimator implementations. This allows for easy substition/comparison of different kernel functions for one another in indicators. Furthermore, kernels can easily be combined with other kernels to create newer, more customized kernels.
rationalQuadratic(_src, _lookback, _relativeWeight, startAtBar)
Rational Quadratic Kernel - An infinite sum of Gaussian Kernels of different length scales.
Parameters:
_src (float) : The source series.
_lookback (simple int) : The number of bars used for the estimation. This is a sliding value that represents the most recent historical bars.
_relativeWeight (simple float) : Relative weighting of time frames. Smaller values resut in a more stretched out curve and larger values will result in a more wiggly curve. As this value approaches zero, the longer time frames will exert more influence on the estimation. As this value approaches infinity, the behavior of the Rational Quadratic Kernel will become identical to the Gaussian kernel.
startAtBar (simple int)
Returns: yhat The estimated values according to the Rational Quadratic Kernel.
gaussian(_src, _lookback, startAtBar)
Gaussian Kernel - A weighted average of the source series. The weights are determined by the Radial Basis Function (RBF).
Parameters:
_src (float) : The source series.
_lookback (simple int) : The number of bars used for the estimation. This is a sliding value that represents the most recent historical bars.
startAtBar (simple int)
Returns: yhat The estimated values according to the Gaussian Kernel.
periodic(_src, _lookback, _period, startAtBar)
Periodic Kernel - The periodic kernel (derived by David Mackay) allows one to model functions which repeat themselves exactly.
Parameters:
_src (float) : The source series.
_lookback (simple int) : The number of bars used for the estimation. This is a sliding value that represents the most recent historical bars.
_period (simple int) : The distance between repititions of the function.
startAtBar (simple int)
Returns: yhat The estimated values according to the Periodic Kernel.
locallyPeriodic(_src, _lookback, _period, startAtBar)
Locally Periodic Kernel - The locally periodic kernel is a periodic function that slowly varies with time. It is the product of the Periodic Kernel and the Gaussian Kernel.
Parameters:
_src (float) : The source series.
_lookback (simple int) : The number of bars used for the estimation. This is a sliding value that represents the most recent historical bars.
_period (simple int) : The distance between repititions of the function.
startAtBar (simple int)
Returns: yhat The estimated values according to the Locally Periodic Kernel.
MLExtensionsRPLibrary "MLExtensionsRP"
A set of extension methods for a novel implementation of a Approximate Nearest Neighbors (ANN) algorithm in Lorentzian space.
normalizeDeriv(src, quadraticMeanLength)
Returns the smoothed hyperbolic tangent of the input series.
Parameters:
src (float) : The input series (i.e., the first-order derivative for price).
quadraticMeanLength (int) : The length of the quadratic mean (RMS).
Returns: nDeriv The normalized derivative of the input series.
normalize(src, min, max)
Rescales a source value with an unbounded range to a target range.
Parameters:
src (float) : The input series
min (float) : The minimum value of the unbounded range
max (float) : The maximum value of the unbounded range
Returns: The normalized series
rescale(src, oldMin, oldMax, newMin, newMax)
Rescales a source value with a bounded range to anther bounded range
Parameters:
src (float) : The input series
oldMin (float) : The minimum value of the range to rescale from
oldMax (float) : The maximum value of the range to rescale from
newMin (float) : The minimum value of the range to rescale to
newMax (float) : The maximum value of the range to rescale to
Returns: The rescaled series
getColorShades(color)
Creates an array of colors with varying shades of the input color
Parameters:
color (color) : The color to create shades of
Returns: An array of colors with varying shades of the input color
getPredictionColor(prediction, neighborsCount, shadesArr)
Determines the color shade based on prediction percentile
Parameters:
prediction (float) : Value of the prediction
neighborsCount (int) : The number of neighbors used in a nearest neighbors classification
shadesArr (array) : An array of colors with varying shades of the input color
Returns: shade Color shade based on prediction percentile
color_green(prediction)
Assigns varying shades of the color green based on the KNN classification
Parameters:
prediction (float) : Value (int|float) of the prediction
Returns: color
color_red(prediction)
Assigns varying shades of the color red based on the KNN classification
Parameters:
prediction (float) : Value of the prediction
Returns: color
tanh(src)
Returns the the hyperbolic tangent of the input series. The sigmoid-like hyperbolic tangent function is used to compress the input to a value between -1 and 1.
Parameters:
src (float) : The input series (i.e., the normalized derivative).
Returns: tanh The hyperbolic tangent of the input series.
dualPoleFilter(src, lookback)
Returns the smoothed hyperbolic tangent of the input series.
Parameters:
src (float) : The input series (i.e., the hyperbolic tangent).
lookback (int) : The lookback window for the smoothing.
Returns: filter The smoothed hyperbolic tangent of the input series.
tanhTransform(src, smoothingFrequency, quadraticMeanLength)
Returns the tanh transform of the input series.
Parameters:
src (float) : The input series (i.e., the result of the tanh calculation).
smoothingFrequency (int)
quadraticMeanLength (int)
Returns: signal The smoothed hyperbolic tangent transform of the input series.
n_rsi(src, n1, n2)
Returns the normalized RSI ideal for use in ML algorithms.
Parameters:
src (float) : The input series (i.e., the result of the RSI calculation).
n1 (simple int) : The length of the RSI.
n2 (simple int) : The smoothing length of the RSI.
Returns: signal The normalized RSI.
n_cci(src, n1, n2)
Returns the normalized CCI ideal for use in ML algorithms.
Parameters:
src (float) : The input series (i.e., the result of the CCI calculation).
n1 (simple int) : The length of the CCI.
n2 (simple int) : The smoothing length of the CCI.
Returns: signal The normalized CCI.
n_wt(src, n1, n2)
Returns the normalized WaveTrend Classic series ideal for use in ML algorithms.
Parameters:
src (float) : The input series (i.e., the result of the WaveTrend Classic calculation).
n1 (simple int)
n2 (simple int)
Returns: signal The normalized WaveTrend Classic series.
n_adx(highSrc, lowSrc, closeSrc, n1)
Returns the normalized ADX ideal for use in ML algorithms.
Parameters:
highSrc (float) : The input series for the high price.
lowSrc (float) : The input series for the low price.
closeSrc (float) : The input series for the close price.
n1 (simple int) : The length of the ADX.
regime_filter(src, threshold, useRegimeFilter)
Parameters:
src (float)
threshold (float)
useRegimeFilter (bool)
filter_adx(src, length, adxThreshold, useAdxFilter)
filter_adx
Parameters:
src (float) : The source series.
length (simple int) : The length of the ADX.
adxThreshold (int) : The ADX threshold.
useAdxFilter (bool) : Whether to use the ADX filter.
Returns: The ADX.
filter_volatility(minLength, maxLength, useVolatilityFilter)
filter_volatility
Parameters:
minLength (simple int) : The minimum length of the ATR.
maxLength (simple int) : The maximum length of the ATR.
useVolatilityFilter (bool) : Whether to use the volatility filter.
Returns: Boolean indicating whether or not to let the signal pass through the filter.
backtest(high, low, open, startLongTrade, endLongTrade, startShortTrade, endShortTrade, isEarlySignalFlip, maxBarsBackIndex, thisBarIndex, src, useWorstCase)
Performs a basic backtest using the specified parameters and conditions.
Parameters:
high (float) : The input series for the high price.
low (float) : The input series for the low price.
open (float) : The input series for the open price.
startLongTrade (bool) : The series of conditions that indicate the start of a long trade.
endLongTrade (bool) : The series of conditions that indicate the end of a long trade.
startShortTrade (bool) : The series of conditions that indicate the start of a short trade.
endShortTrade (bool) : The series of conditions that indicate the end of a short trade.
isEarlySignalFlip (bool) : Whether or not the signal flip is early.
maxBarsBackIndex (int) : The maximum number of bars to go back in the backtest.
thisBarIndex (int) : The current bar index.
src (float) : The source series.
useWorstCase (bool) : Whether to use the worst case scenario for the backtest.
Returns: A tuple containing backtest values
init_table()
init_table()
Returns: tbl The backtest results.
update_table(tbl, tradeStatsHeader, totalTrades, totalWins, totalLosses, winLossRatio, winrate, earlySignalFlips)
update_table(tbl, tradeStats)
Parameters:
tbl (table) : The backtest results table.
tradeStatsHeader (string) : The trade stats header.
totalTrades (float) : The total number of trades.
totalWins (float) : The total number of wins.
totalLosses (float) : The total number of losses.
winLossRatio (float) : The win loss ratio.
winrate (float) : The winrate.
earlySignalFlips (float) : The total number of early signal flips.
Returns: Updated backtest results table.
MLExtensionsLibrary "MLExtensions"
A set of extension methods for a novel implementation of a Approximate Nearest Neighbors (ANN) algorithm in Lorentzian space.
normalizeDeriv(src, quadraticMeanLength)
Returns the smoothed hyperbolic tangent of the input series.
Parameters:
src (float) : The input series (i.e., the first-order derivative for price).
quadraticMeanLength (int) : The length of the quadratic mean (RMS).
Returns: nDeriv The normalized derivative of the input series.
normalize(src, min, max)
Rescales a source value with an unbounded range to a target range.
Parameters:
src (float) : The input series
min (float) : The minimum value of the unbounded range
max (float) : The maximum value of the unbounded range
Returns: The normalized series
rescale(src, oldMin, oldMax, newMin, newMax)
Rescales a source value with a bounded range to anther bounded range
Parameters:
src (float) : The input series
oldMin (float) : The minimum value of the range to rescale from
oldMax (float) : The maximum value of the range to rescale from
newMin (float) : The minimum value of the range to rescale to
newMax (float) : The maximum value of the range to rescale to
Returns: The rescaled series
getColorShades(color)
Creates an array of colors with varying shades of the input color
Parameters:
color (color) : The color to create shades of
Returns: An array of colors with varying shades of the input color
getPredictionColor(prediction, neighborsCount, shadesArr)
Determines the color shade based on prediction percentile
Parameters:
prediction (float) : Value of the prediction
neighborsCount (int) : The number of neighbors used in a nearest neighbors classification
shadesArr (array) : An array of colors with varying shades of the input color
Returns: shade Color shade based on prediction percentile
color_green(prediction)
Assigns varying shades of the color green based on the KNN classification
Parameters:
prediction (float) : Value (int|float) of the prediction
Returns: color
color_red(prediction)
Assigns varying shades of the color red based on the KNN classification
Parameters:
prediction (float) : Value of the prediction
Returns: color
tanh(src)
Returns the the hyperbolic tangent of the input series. The sigmoid-like hyperbolic tangent function is used to compress the input to a value between -1 and 1.
Parameters:
src (float) : The input series (i.e., the normalized derivative).
Returns: tanh The hyperbolic tangent of the input series.
dualPoleFilter(src, lookback)
Returns the smoothed hyperbolic tangent of the input series.
Parameters:
src (float) : The input series (i.e., the hyperbolic tangent).
lookback (int) : The lookback window for the smoothing.
Returns: filter The smoothed hyperbolic tangent of the input series.
tanhTransform(src, smoothingFrequency, quadraticMeanLength)
Returns the tanh transform of the input series.
Parameters:
src (float) : The input series (i.e., the result of the tanh calculation).
smoothingFrequency (int)
quadraticMeanLength (int)
Returns: signal The smoothed hyperbolic tangent transform of the input series.
n_rsi(src, n1, n2)
Returns the normalized RSI ideal for use in ML algorithms.
Parameters:
src (float) : The input series (i.e., the result of the RSI calculation).
n1 (simple int) : The length of the RSI.
n2 (simple int) : The smoothing length of the RSI.
Returns: signal The normalized RSI.
n_cci(src, n1, n2)
Returns the normalized CCI ideal for use in ML algorithms.
Parameters:
src (float) : The input series (i.e., the result of the CCI calculation).
n1 (simple int) : The length of the CCI.
n2 (simple int) : The smoothing length of the CCI.
Returns: signal The normalized CCI.
n_wt(src, n1, n2)
Returns the normalized WaveTrend Classic series ideal for use in ML algorithms.
Parameters:
src (float) : The input series (i.e., the result of the WaveTrend Classic calculation).
n1 (simple int)
n2 (simple int)
Returns: signal The normalized WaveTrend Classic series.
n_adx(highSrc, lowSrc, closeSrc, n1)
Returns the normalized ADX ideal for use in ML algorithms.
Parameters:
highSrc (float) : The input series for the high price.
lowSrc (float) : The input series for the low price.
closeSrc (float) : The input series for the close price.
n1 (simple int) : The length of the ADX.
regime_filter(src, threshold, useRegimeFilter)
Parameters:
src (float)
threshold (float)
useRegimeFilter (bool)
filter_adx(src, length, adxThreshold, useAdxFilter)
filter_adx
Parameters:
src (float) : The source series.
length (simple int) : The length of the ADX.
adxThreshold (int) : The ADX threshold.
useAdxFilter (bool) : Whether to use the ADX filter.
Returns: The ADX.
filter_volatility(minLength, maxLength, useVolatilityFilter)
filter_volatility
Parameters:
minLength (simple int) : The minimum length of the ATR.
maxLength (simple int) : The maximum length of the ATR.
useVolatilityFilter (bool) : Whether to use the volatility filter.
Returns: Boolean indicating whether or not to let the signal pass through the filter.
backtest(high, low, open, startLongTrade, endLongTrade, startShortTrade, endShortTrade, isEarlySignalFlip, maxBarsBackIndex, thisBarIndex, src, useWorstCase)
Performs a basic backtest using the specified parameters and conditions.
Parameters:
high (float) : The input series for the high price.
low (float) : The input series for the low price.
open (float) : The input series for the open price.
startLongTrade (bool) : The series of conditions that indicate the start of a long trade.
endLongTrade (bool) : The series of conditions that indicate the end of a long trade.
startShortTrade (bool) : The series of conditions that indicate the start of a short trade.
endShortTrade (bool) : The series of conditions that indicate the end of a short trade.
isEarlySignalFlip (bool) : Whether or not the signal flip is early.
maxBarsBackIndex (int) : The maximum number of bars to go back in the backtest.
thisBarIndex (int) : The current bar index.
src (float) : The source series.
useWorstCase (bool) : Whether to use the worst case scenario for the backtest.
Returns: A tuple containing backtest values
init_table()
init_table()
Returns: tbl The backtest results.
update_table(tbl, tradeStatsHeader, totalTrades, totalWins, totalLosses, winLossRatio, winrate, earlySignalFlips)
update_table(tbl, tradeStats)
Parameters:
tbl (table) : The backtest results table.
tradeStatsHeader (string) : The trade stats header.
totalTrades (float) : The total number of trades.
totalWins (float) : The total number of wins.
totalLosses (float) : The total number of losses.
winLossRatio (float) : The win loss ratio.
winrate (float) : The winrate.
earlySignalFlips (float) : The total number of early signal flips.
Returns: Updated backtest results table.
KernelSwenLibrary "KernelFunctions"
This library provides non-repainting kernel functions for Nadaraya-Watson estimator implementations. This allows for easy substition/comparison of different kernel functions for one another in indicators. Furthermore, kernels can easily be combined with other kernels to create newer, more customized kernels.
rationalQuadratic(_src, _lookback, _relativeWeight, startAtBar)
Rational Quadratic Kernel - An infinite sum of Gaussian Kernels of different length scales.
Parameters:
_src (float) : The source series.
_lookback (simple int) : The number of bars used for the estimation. This is a sliding value that represents the most recent historical bars.
_relativeWeight (simple float) : Relative weighting of time frames. Smaller values resut in a more stretched out curve and larger values will result in a more wiggly curve. As this value approaches zero, the longer time frames will exert more influence on the estimation. As this value approaches infinity, the behavior of the Rational Quadratic Kernel will become identical to the Gaussian kernel.
startAtBar (simple int)
Returns: yhat The estimated values according to the Rational Quadratic Kernel.
gaussian(_src, _lookback, startAtBar)
Gaussian Kernel - A weighted average of the source series. The weights are determined by the Radial Basis Function (RBF).
Parameters:
_src (float) : The source series.
_lookback (simple int) : The number of bars used for the estimation. This is a sliding value that represents the most recent historical bars.
startAtBar (simple int)
Returns: yhat The estimated values according to the Gaussian Kernel.
periodic(_src, _lookback, _period, startAtBar)
Periodic Kernel - The periodic kernel (derived by David Mackay) allows one to model functions which repeat themselves exactly.
Parameters:
_src (float) : The source series.
_lookback (simple int) : The number of bars used for the estimation. This is a sliding value that represents the most recent historical bars.
_period (simple int) : The distance between repititions of the function.
startAtBar (simple int)
Returns: yhat The estimated values according to the Periodic Kernel.
locallyPeriodic(_src, _lookback, _period, startAtBar)
Locally Periodic Kernel - The locally periodic kernel is a periodic function that slowly varies with time. It is the product of the Periodic Kernel and the Gaussian Kernel.
Parameters:
_src (float) : The source series.
_lookback (simple int) : The number of bars used for the estimation. This is a sliding value that represents the most recent historical bars.
_period (simple int) : The distance between repititions of the function.
startAtBar (simple int)
Returns: yhat The estimated values according to the Locally Periodic Kernel.
SimpleTrendlinesLibrary "SimpleTrendlines"
An accessible and semi-effortless way to draw trendlines with automatic slope and angle calculation.
new(x_axis, offset, strictMode, strictType)
Creates an instance of the trendline library, accepting parameters that allow the library to function accordingly.
Parameters:
x_axis (int) : The x-axis distance between point A and point B.
offset (int) : The offset from x2 and the current bar_index. Used in situations where conditions execute ahead of where the x2 location is, such as pivot events.
strictMode (bool) : Strict mode works in the backend of things to ensure that price hasn't closed below the trendline before the trendline is drawn.
strictType (int) : 0 ensures that price during slope calculation is above line, 1 ensures that price during slope calculation is below line.
method drawLine(this, condition, y1, y2, src)
Draws a new line from the given y-value parameters based on a condition.
Namespace types: Trendline
Parameters:
this (Trendline)
condition (bool) : The condition in order to draw a new line.
y1 (float) : The y-value of point A.
y2 (float) : the y-value of point B.
src (float) : Determines which value strict mode will actively check for leakage before a trendline is drawn.
method drawTrendline(this, condition)
Draws a trendline from the line generated from the drawLine() method.
Namespace types: Trendline
Parameters:
this (Trendline)
condition (bool) : The conditon to maintain the trendline.
TrendlineSettings
The object containing the essential values for proper library execution.
Fields:
x_axis (series int) : The x-axis provided by the user to determine the distance between point A and point B
offset (series int) : The offset from x2 and the current bar_index. Used in situations where conditions execute ahead of where the x2 location is, such as pivot events.
strictMode (series bool) : Strict mode works in the backend to ensure that price hasn't closed below or above the trendline before the trendline is drawn.
strictType (series int) : 0 if price is above line, 1 if price is below line.
TrendlineData
The object containing values that the user can use for further calculation.
Fields:
slope (series float) : The slope of the initial line.
x1 (series int) : The bar_index value of point A.
x2 (series int) : The bar_index value of point B.
y1 (series float)
y2 (series float)
changeInX (series int) : How many bars since the bar_index value of point B.
TrendlineLines
The object containing both the start line and trend line for manipulation.
Fields:
startline (series line) : The initial line that gets drawn when instantiating the drawLine() method.
trendline (series line) : The trendline that gets drawn when instantiating the drawTrendline() method.
Trendline
The object that serves as the class of the library. Inherits all properties and methods.
Fields:
info (TrendlineSettings) : Contains properties inside the TrendlineSettings object.
values (TrendlineData) : Contains properties inside the TrendlineData object.
lines (TrendlineLines) : Contains properties inside the TrendlineLines object.
waves█ OVERVIEW
This library intended for use in Bar Replay provides functions to generate various wave forms (sine, cosine, triangle, square) based on time and customizable parameters. Useful for testing and in creating oscillators, indicators, or visual effects.
█ FUNCTIONS
• getSineWave()
• getCosineWave()
• getTriangleWave()
• getSquareWave()
█ USAGE EXAMPLE
//@version=6
indicator("Wave Example")
import kaigouthro/waves/1
plot(waves.getSineWave(cyclesPerMinute=15))
█ NOTES
* barsPerSecond defaults to 10. Adjust this if not using 10x in Bar Replay.
* Phase shift is in degrees.
---
Library "waves"
getSineWave(cyclesPerMinute, bar, barsPerSecond, amplitude, verticalShift, phaseShift)
`getSineWave`
> Calculates a sine wave based on bar index, cycles per minute (BPM), and wave parameters.
Parameters:
cyclesPerMinute (float) : (float) The desired number of cycles per minute (BPM). Default is 30.0.
bar (int) : (int) The current bar index. Default is bar_index.
barsPerSecond (float) : (float) The number of bars per second. Default is 10.0 for Bar Replay
amplitude (float) : (float) The amplitude of the sine wave. Default is 1.0.
verticalShift (float) : (float) The vertical shift of the sine wave. Default is 0.0.
phaseShift (float) : (float) The phase shift of the sine wave in radians. Default is 0.0.
Returns: (float) The calculated sine wave value.
getCosineWave(cyclesPerMinute, bar, barsPerSecond, amplitude, verticalShift, phaseShift)
`getCosineWave`
> Calculates a cosine wave based on bar index, cycles per minute (BPM), and wave parameters.
Parameters:
cyclesPerMinute (float) : (float) The desired number of cycles per minute (BPM). Default is 30.0.
bar (int) : (int) The current bar index. Default is bar_index.
barsPerSecond (float) : (float) The number of bars per second. Default is 10.0 for Bar Replay
amplitude (float) : (float) The amplitude of the cosine wave. Default is 1.0.
verticalShift (float) : (float) The vertical shift of the cosine wave. Default is 0.0.
phaseShift (float) : (float) The phase shift of the cosine wave in radians. Default is 0.0.
Returns: (float) The calculated cosine wave value.
getTriangleWave(cyclesPerMinute, bar, barsPerSecond, amplitude, verticalShift, phaseShift)
`getTriangleWave`
> Calculates a triangle wave based on bar index, cycles per minute (BPM), and wave parameters.
Parameters:
cyclesPerMinute (float) : (float) The desired number of cycles per minute (BPM). Default is 30.0.
bar (int) : (int) The current bar index. Default is bar_index.
barsPerSecond (float) : (float) The number of bars per second. Default is 10.0 for Bar Replay
amplitude (float) : (float) The amplitude of the triangle wave. Default is 1.0.
verticalShift (float) : (float) The vertical shift of the triangle wave. Default is 0.0.
phaseShift (float) : (float) The phase shift of the triangle wave in radians. Default is 0.0.
Returns: (float) The calculated triangle wave value.
getSquareWave(cyclesPerMinute, bar, barsPerSecond, amplitude, verticalShift, dutyCycle, phaseShift)
`getSquareWave`
> Calculates a square wave based on bar index, cycles per minute (BPM), and wave parameters.
Parameters:
cyclesPerMinute (float) : (float) The desired number of cycles per minute (BPM). Default is 30.0.
bar (int) : (int) The current bar index. Default is bar_index.
barsPerSecond (float) : (float) The number of bars per second. Default is 10.0 for Bar Replay
amplitude (float) : (float) The amplitude of the square wave. Default is 1.0.
verticalShift (float) : (float) The vertical shift of the square wave. Default is 0.0.
dutyCycle (float) : (float) The duty cycle of the square wave (0.0 to 1.0). Default is 0.5 (50% duty cycle).
phaseShift (float) : (float) The phase shift of the square wave in radians. Default is 0.0.
Returns: (float) The calculated square wave value.
KalmanfilterLibrary "Kalmanfilter"
A sophisticated Kalman Filter implementation for financial time series analysis
@author Rocky-Studio
@version 1.0
initialize(initial_value, process_noise, measurement_noise)
Initializes Kalman Filter parameters
Parameters:
initial_value (float) : (float) The initial state estimate
process_noise (float) : (float) The process noise coefficient (Q)
measurement_noise (float) : (float) The measurement noise coefficient (R)
Returns: A tuple containing
update(prev_state, prev_covariance, measurement, process_noise, measurement_noise)
Update Kalman Filter state
Parameters:
prev_state (float)
prev_covariance (float)
measurement (float)
process_noise (float)
measurement_noise (float)
calculate_measurement_noise(price_series, length)
Adaptive measurement noise calculation
Parameters:
price_series (array)
length (int)
calculate_measurement_noise_simple(price_series)
Parameters:
price_series (array)
update_trading(prev_state, prev_velocity, prev_covariance, measurement, volatility_window)
Enhanced trading update with velocity
Parameters:
prev_state (float)
prev_velocity (float)
prev_covariance (float)
measurement (float)
volatility_window (int)
model4_update(prev_mean, prev_speed, prev_covariance, price, process_noise, measurement_noise)
Kalman Filter Model 4 implementation (Benhamou 2018)
Parameters:
prev_mean (float)
prev_speed (float)
prev_covariance (array)
price (float)
process_noise (array)
measurement_noise (float)
model4_initialize(initial_price)
Initialize Model 4 parameters
Parameters:
initial_price (float)
model4_default_process_noise()
Create default process noise matrix for Model 4
model4_calculate_measurement_noise(price_series, length)
Adaptive measurement noise calculation for Model 4
Parameters:
price_series (array)
length (int)
BybitPerpsArrayLibrary "BybitPerpsArray"
f_getSymbolsForGroup(groupName)
Parameters:
groupName (string)
Contains all of the BYBIT Perp charts- use function to call them in groups
pslibs_revisedLibrary "pslibs_revised"
f_calculate_divergence_on_close(close, mom, rsi, start_lookback, max_lookback, rsiThresholdBuy, rsiThresholdSell, minAngleDiff, run_flag)
Parameters:
close (float)
mom (float)
rsi (float)
start_lookback (int)
max_lookback (int)
rsiThresholdBuy (float)
rsiThresholdSell (float)
minAngleDiff (float)
run_flag (bool)
f_calculate_divergence_on_low(low, mom, rsi, start_lookback, max_lookback, rsiThresholdBuy, rsiThresholdSell, minAngleDiff, run_flag)
Parameters:
low (float)
mom (float)
rsi (float)
start_lookback (int)
max_lookback (int)
rsiThresholdBuy (float)
rsiThresholdSell (float)
minAngleDiff (float)
run_flag (bool)
f_calculate_reversal(close, low, high, macdFastPeriod, macdSlowPeriod, macdSignalPeriod, stochPeriod, prcKPeriod, stochOS, stochOB, run_flag)
Parameters:
close (float)
low (float)
high (float)
macdFastPeriod (simple int)
macdSlowPeriod (simple int)
macdSignalPeriod (simple int)
stochPeriod (int)
prcKPeriod (int)
stochOS (int)
stochOB (int)
run_flag (bool)
is_within_first_30_minutes()
is_last_60_minutes()
is_last_30_minutes()
func_yestday_was_postive_trend()
Geo. Geo.
This library provides a comprehensive set of geometric functions based on 2 simple types for point and line manipulation, point array calculations, some vector operations (Borrowed from @ricardosantos ), angle calculations, and basic polygon analysis. It offers tools for creating, transforming, and analyzing geometric shapes and their relationships.
View the source code for detailed documentation on each function and type.
═════════════════════════════════════════════════════════════════════════
█ OVERVIEW
This library enhances TradingView's Pine Script with robust geometric capabilities. It introduces the Point and Line types, along with a suite of functions for various geometric operations. These functionalities empower you to perform advanced calculations, manipulations, and analyses involving points, lines, vectors, angles, and polygons directly within your Pine scripts. The example is at the bottom of the script. ( Commented out )
█ CONCEPTS
This library revolves around two fundamental types:
• Point: Represents a point in 2D space with x and y coordinates, along with optional 'a' (angle) and 'v' (value) fields for versatile use. Crucially, for plotting, utilize the `.to_chart_point()` method to convert Points into plottable chart.point objects.
• Line: Defined by a starting Point and a slope , enabling calculations like getting y for a given x, or finding intersection points.
█ FEATURES
• Point Manipulation: Perform operations like addition, subtraction, scaling, rotation, normalization, calculating distances, dot products, cross products, midpoints, and more with Point objects.
• Line Operations: Create lines, determine their slope, calculate y from x (and vice versa), and find the intersection points of two lines.
• Vector Operations: Perform vector addition, subtraction, multiplication, division, negation, perpendicular vector calculation, floor, fractional part, sine, absolute value, modulus, sign, round, scaling, rescaling, rotation, and ceiling operations.
• Angle Calculations: Compute angles between points in degrees or radians, including signed, unsigned, and 360-degree angles.
• Polygon Analysis: Calculate the area, perimeter, and centroid of polygons. Check if a point is inside a given polygon and determine the convex hull perimeter.
• Chart Plotting: Conveniently convert Point objects to chart.point objects for plotting lines and points on the chart. The library also includes functions for plotting lines between individual and series of points.
• Utility Functions: Includes helper functions such as square root, square, cosine, sine, tangent, arc cosine, arc sine, arc tangent, atan2, absolute distance, golden ratio tolerance check, fractional part, and safe index/check for chart plotting boundaries.
█ HOW TO USE
1 — Include the library in your script using:
import kaigouthro/geo/1
2 — Create Point and Line objects:
p1 = geo.Point(bar_index, close)
p2 = geo.Point(bar_index , open)
myLine = geo.Line(p1, geo.slope(p1, p2))
// maybe use that line to detect a crossing for an alert ... hmmm
3 — Utilize the provided functions:
distance = geo.distance(p1, p2)
intersection = geo.intersection(line1, line2)
4 — For plotting labels, lines, convert Point to chart.point :
label.new(p1.to_chart_point(), " Hi ")
line.new(p1.to_chart_point(),p2.to_chart_point())
█ NOTES
This description provides a concise overview. Consult the library's source code for in-depth documentation, including detailed descriptions, parameter types, and return values for each function and method. The source code is structured with comprehensive comments using the `//@` format for seamless integration with TradingView's auto-documentation features.
█ Possibilities..
Library "geo"
This library provides a comprehensive set of geometric functions and types, including point and line manipulation, vector operations, angle calculations, and polygon analysis. It offers tools for creating, transforming, and analyzing geometric shapes and their relationships.
sqrt(value)
Square root function
Parameters:
value (float) : (float) - The number to take the square root of
Returns: (float) - The square root of the input value
sqr(x)
Square function
Parameters:
x (float) : (float) - The number to square
Returns: (float) - The square of the input value
cos(v)
Cosine function
Parameters:
v (float) : (series float) - The value to find the cosine of
Returns: (series float) - The cosine of the input value
sin(v)
Sine function
Parameters:
v (float) : (series float) - The value to find the sine of
Returns: (series float) - The sine of the input value
tan(v)
Tangent function
Parameters:
v (float) : (series float) - The value to find the tangent of
Returns: (series float) - The tangent of the input value
acos(v)
Arc cosine function
Parameters:
v (float) : (series float) - The value to find the arc cosine of
Returns: (series float) - The arc cosine of the input value
asin(v)
Arc sine function
Parameters:
v (float) : (series float) - The value to find the arc sine of
Returns: (series float) - The arc sine of the input value
atan(v)
Arc tangent function
Parameters:
v (float) : (series float) - The value to find the arc tangent of
Returns: (series float) - The arc tangent of the input value
atan2(dy, dx)
atan2 function
Parameters:
dy (float) : (float) - The y-coordinate
dx (float) : (float) - The x-coordinate
Returns: (float) - The angle in radians
gap(_value1, __value2)
Absolute distance between any two float values
Parameters:
_value1 (float) : First value
__value2 (float)
Returns: Absolute Positive Distance
phi_tol(a, b, tolerance)
Check if the ratio is within the tolerance of the golden ratio
Parameters:
a (float) : (float) The first number
b (float) : (float) The second number
tolerance (float) : (float) The tolerance percennt as 1 = 1 percent
Returns: (bool) True if the ratio is within the tolerance, false otherwise
frac(x)
frad Fractional
Parameters:
x (float) : (float) - The number to convert to fractional
Returns: (float) - The number converted to fractional
safeindex(x, limit)
limiting int to hold the value within the chart range
Parameters:
x (float) : (float) - The number to limit
limit (int)
Returns: (int) - The number limited to the chart range
safecheck(x, limit)
limiting int check if within the chartplottable range
Parameters:
x (float) : (float) - The number to limit
limit (int)
Returns: (int) - The number limited to the chart range
interpolate(a, b, t)
interpolate between two values
Parameters:
a (float) : (float) - The first value
b (float) : (float) - The second value
t (float) : (float) - The interpolation factor (0 to 1)
Returns: (float) - The interpolated value
gcd(_numerator, _denominator)
Greatest common divisor of two integers
Parameters:
_numerator (int)
_denominator (int)
Returns: (int) The greatest common divisor
method set_x(self, value)
Set the x value of the point, and pass point for chaining
Namespace types: Point
Parameters:
self (Point) : (Point) The point to modify
value (float) : (float) The new x-coordinate
method set_y(self, value)
Set the y value of the point, and pass point for chaining
Namespace types: Point
Parameters:
self (Point) : (Point) The point to modify
value (float) : (float) The new y-coordinate
method get_x(self)
Get the x value of the point
Namespace types: Point
Parameters:
self (Point) : (Point) The point to get the x-coordinate from
Returns: (float) The x-coordinate
method get_y(self)
Get the y value of the point
Namespace types: Point
Parameters:
self (Point) : (Point) The point to get the y-coordinate from
Returns: (float) The y-coordinate
method vmin(self)
Lowest element of the point
Namespace types: Point
Parameters:
self (Point) : (Point) The point
Returns: (float) The lowest value between x and y
method vmax(self)
Highest element of the point
Namespace types: Point
Parameters:
self (Point) : (Point) The point
Returns: (float) The highest value between x and y
method add(p1, p2)
Addition
Namespace types: Point
Parameters:
p1 (Point) : (Point) - The first point
p2 (Point) : (Point) - The second point
Returns: (Point) - the add of the two points
method sub(p1, p2)
Subtraction
Namespace types: Point
Parameters:
p1 (Point) : (Point) - The first point
p2 (Point) : (Point) - The second point
Returns: (Point) - the sub of the two points
method mul(p, scalar)
Multiplication by scalar
Namespace types: Point
Parameters:
p (Point) : (Point) - The point
scalar (float) : (float) - The scalar to multiply by
Returns: (Point) - the multiplied point of the point and the scalar
method div(p, scalar)
Division by scalar
Namespace types: Point
Parameters:
p (Point) : (Point) - The point
scalar (float) : (float) - The scalar to divide by
Returns: (Point) - the divided point of the point and the scalar
method rotate(p, angle)
Rotate a point around the origin by an angle (in degrees)
Namespace types: Point
Parameters:
p (Point) : (Point) - The point to rotate
angle (float) : (float) - The angle to rotate by in degrees
Returns: (Point) - the rotated point
method length(p)
Length of the vector from origin to the point
Namespace types: Point
Parameters:
p (Point) : (Point) - The point
Returns: (float) - the length of the point
method length_squared(p)
Length squared of the vector
Namespace types: Point
Parameters:
p (Point) : (Point) The point
Returns: (float) The squared length of the point
method normalize(p)
Normalize the point to a unit vector
Namespace types: Point
Parameters:
p (Point) : (Point) - The point to normalize
Returns: (Point) - the normalized point
method dot(p1, p2)
Dot product
Namespace types: Point
Parameters:
p1 (Point) : (Point) - The first point
p2 (Point) : (Point) - The second point
Returns: (float) - the dot of the two points
method cross(p1, p2)
Cross product result (in 2D, this is a scalar)
Namespace types: Point
Parameters:
p1 (Point) : (Point) - The first point
p2 (Point) : (Point) - The second point
Returns: (float) - the cross of the two points
method distance(p1, p2)
Distance between two points
Namespace types: Point
Parameters:
p1 (Point) : (Point) - The first point
p2 (Point) : (Point) - The second point
Returns: (float) - the distance of the two points
method Point(x, y, a, v)
Point Create Convenience
Namespace types: series float, simple float, input float, const float
Parameters:
x (float)
y (float)
a (float)
v (float)
Returns: (Point) new point
method angle(p1, p2)
Angle between two points in degrees
Namespace types: Point
Parameters:
p1 (Point) : (Point) - The first point
p2 (Point) : (Point) - The second point
Returns: (float) - the angle of the first point and the second point
method angle_between(p, pivot, other)
Angle between two points in degrees from a pivot point
Namespace types: Point
Parameters:
p (Point) : (Point) - The point to calculate the angle from
pivot (Point) : (Point) - The pivot point
other (Point) : (Point) - The other point
Returns: (float) - the angle between the two points
method translate(p, from_origin, to_origin)
Translate a point from one origin to another
Namespace types: Point
Parameters:
p (Point) : (Point) - The point to translate
from_origin (Point) : (Point) - The origin to translate from
to_origin (Point) : (Point) - The origin to translate to
Returns: (Point) - the translated point
method midpoint(p1, p2)
Midpoint of two points
Namespace types: Point
Parameters:
p1 (Point) : (Point) - The first point
p2 (Point) : (Point) - The second point
Returns: (Point) - The midpoint of the two points
method rotate_around(p, angle, pivot)
Rotate a point around a pivot point by an angle (in degrees)
Namespace types: Point
Parameters:
p (Point) : (Point) - The point to rotate
angle (float) : (float) - The angle to rotate by in degrees
pivot (Point) : (Point) - The pivot point to rotate around
Returns: (Point) - the rotated point
method multiply(_a, _b)
Multiply vector _a with _b
Namespace types: Point
Parameters:
_a (Point) : (Point) The first point
_b (Point) : (Point) The second point
Returns: (Point) The result of the multiplication
method divide(_a, _b)
Divide vector _a by _b
Namespace types: Point
Parameters:
_a (Point) : (Point) The first point
_b (Point) : (Point) The second point
Returns: (Point) The result of the division
method negate(_a)
Negative of vector _a
Namespace types: Point
Parameters:
_a (Point) : (Point) The point to negate
Returns: (Point) The negated point
method perp(_a)
Perpendicular Vector of _a
Namespace types: Point
Parameters:
_a (Point) : (Point) The point
Returns: (Point) The perpendicular point
method vfloor(_a)
Compute the floor of argument vector _a
Namespace types: Point
Parameters:
_a (Point) : (Point) The point
Returns: (Point) The floor of the point
method fractional(_a)
Compute the fractional part of the elements from vector _a
Namespace types: Point
Parameters:
_a (Point) : (Point) The point
Returns: (Point) The fractional part of the point
method vsin(_a)
Compute the sine of argument vector _a
Namespace types: Point
Parameters:
_a (Point) : (Point) The point
Returns: (Point) The sine of the point
lcm(a, b)
Least common multiple of two integers
Parameters:
a (int) : (int) The first integer
b (int) : (int) The second integer
Returns: (int) The least common multiple
method vabs(_a)
Compute the absolute of argument vector _a
Namespace types: Point
Parameters:
_a (Point) : (Point) The point
Returns: (Point) The absolute of the point
method vmod(_a, _b)
Compute the mod of argument vector _a
Namespace types: Point
Parameters:
_a (Point) : (Point) The point
_b (float) : (float) The mod
Returns: (Point) The mod of the point
method vsign(_a)
Compute the sign of argument vector _a
Namespace types: Point
Parameters:
_a (Point) : (Point) The point
Returns: (Point) The sign of the point
method vround(_a)
Compute the round of argument vector _a
Namespace types: Point
Parameters:
_a (Point) : (Point) The point
Returns: (Point) The round of the point
method normalize_y(p, height)
normalizes the y value of a point to an input height
Namespace types: Point
Parameters:
p (Point) : (Point) - The point to normalize
height (float) : (float) - The height to normalize to
Returns: (Point) - the normalized point
centroid(points)
Calculate the centroid of multiple points
Parameters:
points (array) : (array) The array of points
Returns: (Point) The centroid point
random_point(_height, _width, _origin, _centered)
Random Point in a given height and width
Parameters:
_height (float) : (float) The height of the area to generate the point in
_width (float) : (float) The width of the area to generate the point in
_origin (Point) : (Point) The origin of the area to generate the point in (default: na, will create a Point(0, 0))
_centered (bool) : (bool) Center the origin point in the area, otherwise, positive h/w (default: false)
Returns: (Point) The random point in the given area
random_point_array(_origin, _height, _width, _centered, _count)
Random Point Array in a given height and width
Parameters:
_origin (Point) : (Point) The origin of the area to generate the array (default: na, will create a Point(0, 0))
_height (float) : (float) The height of the area to generate the array
_width (float) : (float) The width of the area to generate the array
_centered (bool) : (bool) Center the origin point in the area, otherwise, positive h/w (default: false)
_count (int) : (int) The number of points to generate (default: 50)
Returns: (array) The random point array in the given area
method sort_points(points, by_x)
Sorts an array of points by x or y coordinate
Namespace types: array
Parameters:
points (array) : (array) The array of points to sort
by_x (bool) : (bool) Whether to sort by x-coordinate (true) or y-coordinate (false)
Returns: (array) The sorted array of points
method equals(_a, _b)
Compares two points for equality
Namespace types: Point
Parameters:
_a (Point) : (Point) The first point
_b (Point) : (Point) The second point
Returns: (bool) True if the points are equal, false otherwise
method max(origin, _a, _b)
Maximum of two points from origin, using dot product
Namespace types: Point
Parameters:
origin (Point)
_a (Point) : (Point) The first point
_b (Point) : (Point) The second point
Returns: (Point) The maximum point
method min(origin, _a, _b)
Minimum of two points from origin, using dot product
Namespace types: Point
Parameters:
origin (Point)
_a (Point) : (Point) The first point
_b (Point) : (Point) The second point
Returns: (Point) The minimum point
method avg_x(points)
Average x of point array
Namespace types: array
Parameters:
points (array) : (array) The array of points
Returns: (float) The average x-coordinate
method avg_y(points)
Average y of point array
Namespace types: array
Parameters:
points (array) : (array) The array of points
Returns: (float) The average y-coordinate
method range_x(points)
Range of x values in point array
Namespace types: array
Parameters:
points (array) : (array) The array of points
Returns: (float) The range of x-coordinates
method range_y(points)
Range of y values in point array
Namespace types: array
Parameters:
points (array) : (array) The array of points
Returns: (float) The range of y-coordinates
method max_x(points)
max of x values in point array
Namespace types: array
Parameters:
points (array) : (array) The array of points
Returns: (float) The max of x-coordinates
method min_y(points)
min of x values in point array
Namespace types: array
Parameters:
points (array) : (array) The array of points
Returns: (float) The min of x-coordinates
method scale(_a, _scalar)
Scale a point by a scalar
Namespace types: Point
Parameters:
_a (Point) : (Point) The point to scale
_scalar (float) : (float) The scalar value
Returns: (Point) The scaled point
method rescale(_a, _length)
Rescale a point to a new magnitude
Namespace types: Point
Parameters:
_a (Point) : (Point) The point to rescale
_length (float) : (float) The new magnitude
Returns: (Point) The rescaled point
method rotate_rad(_a, _radians)
Rotate a point by an angle in radians
Namespace types: Point
Parameters:
_a (Point) : (Point) The point to rotate
_radians (float) : (float) The angle in radians
Returns: (Point) The rotated point
method rotate_degree(_a, _degree)
Rotate a point by an angle in degrees
Namespace types: Point
Parameters:
_a (Point) : (Point) The point to rotate
_degree (float) : (float) The angle in degrees
Returns: (Point) The rotated point
method vceil(_a, _digits)
Ceil a point to a certain number of digits
Namespace types: Point
Parameters:
_a (Point) : (Point) The point to ceil
_digits (int) : (int) The number of digits to ceil to
Returns: (Point) The ceiled point
method vpow(_a, _exponent)
Raise both point elements to a power
Namespace types: Point
Parameters:
_a (Point) : (Point) The point
_exponent (float) : (float) The exponent
Returns: (Point) The point with elements raised to the power
method perpendicular_distance(_a, _b, _c)
Distance from point _a to line between _b and _c
Namespace types: Point
Parameters:
_a (Point) : (Point) The point
_b (Point) : (Point) The start point of the line
_c (Point) : (Point) The end point of the line
Returns: (float) The perpendicular distance
method project(_a, _axis)
Project a point onto another
Namespace types: Point
Parameters:
_a (Point) : (Point) The point to project
_axis (Point) : (Point) The point to project onto
Returns: (Point) The projected point
method projectN(_a, _axis)
Project a point onto a point of unit length
Namespace types: Point
Parameters:
_a (Point) : (Point) The point to project
_axis (Point) : (Point) The unit length point to project onto
Returns: (Point) The projected point
method reflect(_a, _axis)
Reflect a point on another
Namespace types: Point
Parameters:
_a (Point) : (Point) The point to reflect
_axis (Point) : (Point) The point to reflect on
Returns: (Point) The reflected point
method reflectN(_a, _axis)
Reflect a point to an arbitrary axis
Namespace types: Point
Parameters:
_a (Point) : (Point) The point to reflect
_axis (Point) : (Point) The axis to reflect to
Returns: (Point) The reflected point
method angle_rad(_a)
Angle in radians of a point
Namespace types: Point
Parameters:
_a (Point) : (Point) The point
Returns: (float) The angle in radians
method angle_unsigned(_a, _b)
Unsigned degree angle between 0 and +180 by given two points
Namespace types: Point
Parameters:
_a (Point) : (Point) The first point
_b (Point) : (Point) The second point
Returns: (float) The unsigned angle in degrees
method angle_signed(_a, _b)
Signed degree angle between -180 and +180 by given two points
Namespace types: Point
Parameters:
_a (Point) : (Point) The first point
_b (Point) : (Point) The second point
Returns: (float) The signed angle in degrees
method angle_360(_a, _b)
Degree angle between 0 and 360 by given two points
Namespace types: Point
Parameters:
_a (Point) : (Point) The first point
_b (Point) : (Point) The second point
Returns: (float) The angle in degrees (0-360)
method clamp(_a, _vmin, _vmax)
Restricts a point between a min and max value
Namespace types: Point
Parameters:
_a (Point) : (Point) The point to restrict
_vmin (Point) : (Point) The minimum point
_vmax (Point) : (Point) The maximum point
Returns: (Point) The restricted point
method lerp(_a, _b, _rate_of_move)
Linearly interpolates between points a and b by _rate_of_move
Namespace types: Point
Parameters:
_a (Point) : (Point) The starting point
_b (Point) : (Point) The ending point
_rate_of_move (float) : (float) The rate of movement (0-1)
Returns: (Point) The interpolated point
method slope(p1, p2)
Slope of a line between two points
Namespace types: Point
Parameters:
p1 (Point) : (Point) - The first point
p2 (Point) : (Point) - The second point
Returns: (float) - The slope of the line
method gety(self, x)
Get y-coordinate of a point on the line given its x-coordinate
Namespace types: Line
Parameters:
self (Line) : (Line) - The line
x (float) : (float) - The x-coordinate
Returns: (float) - The y-coordinate
method getx(self, y)
Get x-coordinate of a point on the line given its y-coordinate
Namespace types: Line
Parameters:
self (Line) : (Line) - The line
y (float) : (float) - The y-coordinate
Returns: (float) - The x-coordinate
method intersection(self, other)
Intersection point of two lines
Namespace types: Line
Parameters:
self (Line) : (Line) - The first line
other (Line) : (Line) - The second line
Returns: (Point) - The intersection point
method calculate_arc_point(self, b, p3)
Calculate a point on the arc defined by three points
Namespace types: Point
Parameters:
self (Point) : (Point) The starting point of the arc
b (Point) : (Point) The middle point of the arc
p3 (Point) : (Point) The end point of the arc
Returns: (Point) A point on the arc
approximate_center(point1, point2, point3)
Approximate the center of a spiral using three points
Parameters:
point1 (Point) : (Point) The first point
point2 (Point) : (Point) The second point
point3 (Point) : (Point) The third point
Returns: (Point) The approximate center point
createEdge(center, radius, angle)
Get coordinate from center by radius and angle
Parameters:
center (Point) : (Point) - The center point
radius (float) : (float) - The radius of the circle
angle (float) : (float) - The angle in degrees
Returns: (Point) - The coordinate on the circle
getGrowthFactor(p1, p2, p3)
Get growth factor of spiral point
Parameters:
p1 (Point) : (Point) - The first point
p2 (Point) : (Point) - The second point
p3 (Point) : (Point) - The third point
Returns: (float) - The growth factor
method to_chart_point(point)
Convert Point to chart.point using chart.point.from_index(safeindex(point.x), point.y)
Namespace types: Point
Parameters:
point (Point) : (Point) - The point to convert
Returns: (chart.point) - The chart.point representation of the input point
method plotline(p1, p2, col, width)
Draw a line from p1 to p2
Namespace types: Point
Parameters:
p1 (Point) : (Point) First point
p2 (Point) : (Point) Second point
col (color)
width (int)
Returns: (line) Line object
method drawlines(points, col, ignore_boundary)
Draw lines between points in an array
Namespace types: array
Parameters:
points (array) : (array) The array of points
col (color) : (color) The color of the lines
ignore_boundary (bool) : (bool) The color of the lines
method to_chart_points(points)
Draw an array of points as chart points on the chart with line.new(chartpoint1, chartpoint2, color=linecolor)
Namespace types: array
Parameters:
points (array) : (array) - The points to draw
Returns: (array) The array of chart points
polygon_area(points)
Calculate the area of a polygon defined by an array of points
Parameters:
points (array) : (array) The array of points representing the polygon vertices
Returns: (float) The area of the polygon
polygon_perimeter(points)
Calculate the perimeter of a polygon
Parameters:
points (array) : (array) Array of points defining the polygon
Returns: (float) Perimeter of the polygon
is_point_in_polygon(point, _polygon)
Check if a point is inside a polygon
Parameters:
point (Point) : (Point) The point to check
_polygon (array)
Returns: (bool) True if the point is inside the polygon, false otherwise
method perimeter(points)
Calculates the convex hull perimeter of a set of points
Namespace types: array
Parameters:
points (array) : (array) The array of points
Returns: (array) The array of points forming the convex hull perimeter
Point
A Point, can be used for vector, floating calcs, etc. Use the cp method for plots
Fields:
x (series float) : (float) The x-coordinate
y (series float) : (float) The y-coordinate
a (series float) : (float) An Angle storage spot
v (series float) : (float) A Value
Line
Line
Fields:
point (Point) : (Point) The starting point of the line
slope (series float) : (float) The slope of the line
GOMTRY.
lib_statemachine_modifiedLibrary "lib_statemachine_modified"
Modified to fix bugs and create getState and priorState methods.
method step(this, before, after, condition)
Namespace types: StateMachine
Parameters:
this (StateMachine)
before (int) : (int): Current state before transition
after (int) : (int): State to transition to
condition (bool) : (bool): Condition to trigger the transition
Returns: (bool): True if the state changed, else False
method step(this, after, condition)
Namespace types: StateMachine
Parameters:
this (StateMachine)
after (int) : (int): State to transition to
condition (bool) : (bool): Condition to trigger the transition
Returns: (bool): True if the state changed, else False
method currentState(this)
Namespace types: StateMachine
Parameters:
this (StateMachine)
method previousState(this)
Namespace types: StateMachine
Parameters:
this (StateMachine)
method changed(this, within_bars)
Namespace types: StateMachine
Parameters:
this (StateMachine)
within_bars (int) : (int): Number of bars to look back for a state change
Returns: (bool): True if a state change occurred within the timeframe, else False
method reset(this, condition, min_occurrences)
Namespace types: StateMachine
Parameters:
this (StateMachine)
condition (bool) : (bool): Condition to trigger the reset
min_occurrences (int) : (int): Minimum number of times the condition must be true to reset
Returns: (bool): True if the state was reset, else False
StateMachine
Fields:
state (series int)
neutral (series int)
enabled (series bool)
reset_counter (series int)
prior_state (series int)
last_change_bar (series int)
KwakPineHelperLibrary "KwakPineHelper"
TODO: add library description here
fun(x)
TODO: add function description here
Parameters:
x (float) : TODO: add parameter x description here
Returns: TODO: add what function returns
all_opentrades_size()
get all opentrades size
Returns: (float) size
recent_opentrade_profit()
get recent opentrade profit
Returns: (float) profit
all_opentrades_profit()
get all opentrades profit
Returns: (float) profit
recent_closedtrade_profit()
get recent closedtrade profit
Returns: (float) profit
recent_opentrade_max_runup()
get recent opentrade max runup
Returns: (float) runup
recent_closedtrade_max_runup()
get recent closedtrade max runup
Returns: (float) runup
recent_opentrade_max_drawdown()
get recent opentrade maxdrawdown
Returns: (float) mdd
recent_closedtrade_max_drawdown()
get recent closedtrade maxdrawdown
Returns: (float) mdd
max_open_trades_drawdown()
get max open trades drawdown
Returns: (float) mdd
recent_opentrade_commission()
get recent opentrade commission
Returns: (float) commission
recent_closedtrade_commission()
get recent closedtrade commission
Returns: (float) commission
qty_by_percent_of_equity(percent)
get qty by percent of equtiy
Parameters:
percent (float) : (series float) percent that you want to set
Returns: (float) quantity
qty_by_percent_of_position_size(percent)
get size by percent of position size
Parameters:
percent (float) : (series float) percent that you want to set
Returns: (float) size
is_day_change()
get bool change of day
Returns: (bool) day is change or not
is_in_trade(numberOfBars)
get bool using number of bars
Parameters:
numberOfBars (int)
Returns: (bool) allowedToTrade
api_msg_system(chat_id, message)
Parameters:
chat_id (string)
message (string)
is_first_day()
Check if today is the first day
Returns: (bool) true if today is the first day, false otherwise
is_last_day()
Check if today is the last day
Returns: (bool) true if today is the last day, false otherwise
is_entry()
Check if trade is open
Returns: (bool) true if trade is open, false otherwise
is_close()
Check if trade is closed
Returns: (bool) true if trade is closed, false otherwise
is_win()
Check if trade is win
Returns: (bool) true if trade is win, false otherwise
is_loss()
Check if trade is loss
Returns: (bool) true if trade is loss, false otherwise
permutation█ OVERVIEW
This library provides functions for generating permutations of string or float arrays, using an iterative approach where pine has no recursion. It supports allowing/limiting duplicate elements and handles large result sets by segmenting them into manageable chunks within custom Data types. The most combinations will vary, but the highest is around 250,000 unique combinations. depending on input array values and output length. it will return nothing if the input count is too low.
█ CONCEPTS
This library addresses two key challenges in Pine Script:
• Recursion Depth Limits: Pine has limitations on recursion depth. This library uses an iterative, stack-based algorithm to generate permutations, avoiding recursive function calls that could exceed these limits.
• Array Size Limits: Pine arrays have size restrictions. This library manages large permutation sets by dividing them into smaller segments stored within a custom Data or DataFloat type, using maps for efficient access.
█ HOW TO USE
1 — Include the Library: Add this library to your script using:
import kaigouthro/permutation/1 as permute
2 — Call the generatePermutations Function:
stringPermutations = permute.generatePermutations(array.from("a", "b", "c"), 2, 1)
floatPermutations = permute.generatePermutations(array.from(1.0, 2.0, 3.0), 2, 1)
• set : The input array of strings or floats.
• size : The desired length of each permutation.
• maxDuplicates (optional): The maximum allowed repetitions of an element within a single permutation. Defaults to 1.
3 — Access the Results: The function returns a Data (for strings) or DataFloat (for floats) object. These objects contain:
• data : An array indicating which segments are present (useful for iterating).
• segments : A map where keys represent segment indices and values are the actual permutation data within that segment.
Example: Accessing Permutations
for in stringPermutations.segments
for in currentSegment.segments
// Access individual permutations within the segment.
permutation = segmennt.data
for item in permutation
// Use the permutation elements...
█ TYPES
• PermutationState / PermutationStateFloat : Internal types used by the iterative algorithm to track the state of permutation generation.
• Data / DataFloat : Custom types to store and manage the generated permutations in segments.
█ NOTES
* The library prioritizes handling potentially large permutation sets. 250,000 i about the highest achievable.
* The segmentation logic ensures that results are accessible even when the total number of permutations exceeds Pine's array size limits.
----
Library "permutation"
This library provides functions for generating permutations of user input arrays containing either strings or floats. It uses an iterative, stack-based approach to handle potentially large sets and avoid recursion limitation. The library supports limiting the number of duplicate elements allowed in each permutation. Results are stored in a custom Data or DataFloat type that uses maps to segment large permutation sets into manageable chunks, addressing Pine Script's array size limitations.
generatePermutations(set, size, maxDuplicates)
> Generates permutations of a given size from a set of strings or floats.
Parameters:
set (array) : (array or array) The set of strings or floats to generate permutations from.
size (int) : (int) The size of the permutations to generate.
maxDuplicates (int) : (int) The maximum number of times an element can be repeated in a permutation.
Returns: (Data or DataFloat) A Data object for strings or a DataFloat object for floats, containing the generated permutations.
stringPermutations = generatePermutations(array.from("a", "b", "c"), 2, 1)
floatPermutations = generatePermutations(array.from(1.0, 2.0, 3.0), 2, 1)
generatePermutations(set, size, maxDuplicates)
Parameters:
set (array)
size (int)
maxDuplicates (int)
PermutationState
PermutationState
Fields:
data (array) : (array) The current permutation being built.
index (series int) : (int) The current index being considered in the set.
depth (series int) : (int) The current depth of the permutation (number of elements).
counts (map) : (map) Map to track the count of each element in the current permutation (for duplicates).
PermutationStateFloat
PermutationStateFloat
Fields:
data (array) : (array) The current permutation being built.
index (series int) : (int) The current index being considered in the set.
depth (series int) : (int) The current depth of the permutation (number of elements).
counts (map) : (map) Map to track the count of each element in the current permutation (for duplicates).
Data
Data
Fields:
data (array) : (array) Array to indicate which segments are present.
segments (map) : (map) Map to store permutation segments. Each segment contains a subset of the generated permutations.
DataFloat
DataFloat
Fields:
data (array) : (array) Array to indicate which segments are present.
segments (map) : (map) Map to store permutation segments. Each segment contains a subset of the generated permutations.
random_values█ OVERVIEW
This library provides helper functions for generating random values of various types, including numbers, letters, words, booleans, and arrays. It simplifies the creation of random data within Pine Script™ for testing, simulations, or other applications.
█ HOW TO USE
Import the library into your script:
import kaigouthro/random_values/1 as rv
Then, use the functions provided:
// Get a random integer between 5 and 15
int randInt = rv.intVal(5, 15)
// Generate a random word with 8 characters
string randWord = rv.word(8)
// Create a boolean array with 5 elements
array randBoolArray = rv.boolArray(5)
// And other options! See below for details.
█ FEATURES
• num(float min, float max) : Returns a random float between *min* and *max*. (Internal helper function, not exported).
• letter() : Returns a random lowercase letter (a-z).
• word(int size = 0) : Returns a random word. *size* specifies the length (default: random length between 3 and 10).
• words(int size = 20) : Returns a string of random words separated by spaces, where *size* specifies the number of words.
• boolVal() : Returns a random boolean (true or false).
• floatVal(float min = 0, float max = 100, int precision = 2) : Returns a random float with specified *min*, *max*, and *precision*.
• intVal(int min = 1, int max = 100) : Returns a random integer between *min* and *max*.
• stringArray(int size = 0) : Returns an array of random words. *size* specifies the array length (default: random between 3 and 10).
• floatArray(int size = 0, float min = 0, float max = 100, int precision = 2) : Returns an array of random floats with specified parameters. *size* determines the array length.
• intArray(int size = 0, int min = 1, int max = 100) : Returns an array of random integers with specified parameters. *size* determines the array length.
• boolArray(int size = 0) : Returns an array of random booleans. *size* specifies the array length (default: random between 3 and 10).
█ NOTES
* This library uses the `kaigouthro/into/2` library for type conversions. Make sure it's available.
* Default values are provided for most function parameters, offering flexibility in usage.
█ LICENSE
This Pine Script™ code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org
```
**Changes and Rationale:**
* **OVERVIEW:** Clearly states the library's purpose.
* **HOW TO USE:** Provides essential import and usage instructions with Pine Script™ examples.
* **FEATURES:** Details each function with its parameters, types, and descriptions. Emphasizes *size*, *min*, *max*, and *precision* as common input parameters using italics. Uses custom bulleted lists.
* **NOTES:** Includes important information about dependencies and defaults.
* **LICENSE:** Directly links to the license URL using the proper ` ` tag.
* **Formatting:** Uses full block and em space for section titles, consistent bolding, and improved spacing for readability. Removes unnecessary blank lines.
This format improves clarity, making the library documentation easy to understand for TradingView users. Remember to test the rendering on TradingView to catch any formatting issues.
Library "random_values"
A library containing Random value generating helper functions.
letter()
Random letter generator.
Returns: (string) A random lowercase letter.
word(size)
Random word generator.
Parameters:
size (int) : (int) The desired length of the word. If 0 or not provided, a random length between 3 and 10 is used.
Returns: (string) A random word.
words(size)
Random words generator.
Parameters:
size (int) : (int) The number of words to generate. If 0 or not provided, a random number between 3 and 10 is used.
Returns: (string) A string of random words separated by spaces.
boolVal()
Random boolean generator.
Returns: (bool) A random boolean value (true or false).
floatVal(min, max, precision)
Random float number generator.
Parameters:
min (float) : (float) The minimum float value. Defaults to 0.
max (float) : (float) The maximum float value. Defaults to 100.
precision (int) : (int) The number of decimal places. Defaults to 2.
Returns: (float) A random float number.
intVal(min, max)
Random integer number generator.
Parameters:
min (int) : (int) The minimum integer value. Defaults to 1.
max (int) : (int) The maximum integer value. Defaults to 100.
Returns: (int) A random integer number.
stringArray(size)
Random string array generator.
Parameters:
size (int) : (int) The desired size of the array. If 0 or not provided, a random size between 3 and 10 is used.
Returns: (array) An array of random words.
floatArray(size, min, max, precision)
Random float array generator.
Parameters:
size (int) : (int) The desired size of the array. If 0 or not provided, a random size between 3 and 10 is used.
min (float) : (float) The minimum float value. Defaults to 0.
max (float) : (float) The maximum float value. Defaults to 100.
precision (int) : (int) The number of decimal places. Defaults to 2.
Returns: (array) An array of random float numbers.
intArray(size, min, max)
Random integer array generator.
Parameters:
size (int) : (int) The desired size of the array. If 0 or not provided, a random size between 3 and 10 is used.
min (int) : (int) The minimum integer value. Defaults to 1.
max (int) : (int) The maximum integer value. Defaults to 100.
Returns: (array) An array of random integer numbers.
boolArray(size)
Random boolean array generator.
Parameters:
size (int) : (int) The desired size of the array. If 0 or not provided, a random size between 3 and 10 is used.
Returns: (array) An array of random boolean values.
metaconnectorLibrary "metaconnector"
metaconnector
buy_market_order(License_ID, symbol, lot)
Places a buy market order
Parameters:
License_ID (string) : Unique license ID of the user
symbol (string) : Trading symbol
lot (int) : Number of lots to buy
Returns: String syntax for the buy market order
sell_market_order(License_ID, symbol, lot)
Places a sell market order
Parameters:
License_ID (string) : Unique license ID of the user
symbol (string) : Trading symbol
lot (int) : Number of lots to sell
Returns: String syntax for the sell market order
buy_limit_order(License_ID, symbol, lot, price)
Places a buy limit order
Parameters:
License_ID (string) : Unique license ID of the user
symbol (string) : Trading symbol
lot (int) : Number of lots to buy
price (float) : Limit price for the order
Returns: String syntax for the buy limit order
sell_limit_order(License_ID, symbol, lot, price)
Places a sell limit order
Parameters:
License_ID (string) : Unique license ID of the user
symbol (string) : Trading symbol
lot (int) : Number of lots to sell
price (float) : Limit price for the order
Returns: String syntax for the sell limit order
stoploss_for_buy_order(License_ID, symbol, lot, stoploss_price)
Places a stop-loss order for a buy position
Parameters:
License_ID (string) : Unique license ID of the user
symbol (string) : Trading symbol
lot (int) : Number of lots to buy
stoploss_price (float)
Returns: String syntax for the buy stop-loss order
stoploss_for_sell_order(License_ID, symbol, lot, stoploss_price)
Places a stop-loss order for a sell position
Parameters:
License_ID (string) : Unique license ID of the user
symbol (string) : Trading symbol
lot (int) : Number of lots to sell
stoploss_price (float)
Returns: String syntax for the sell stop-loss order
takeprofit_for_buy_order(License_ID, symbol, lot, target_price)
Places a take-profit order for a buy position
Parameters:
License_ID (string) : Unique license ID of the user
symbol (string) : Trading symbol
lot (int) : Number of lots to buy
target_price (float)
Returns: String syntax for the buy take-profit order
takeprofit_for_sell_order(License_ID, symbol, lot, target_price)
Places a take-profit order for a sell position
Parameters:
License_ID (string) : Unique license ID of the user
symbol (string) : Trading symbol
lot (int) : Number of lots to sell
target_price (float)
Returns: String syntax for the sell take-profit order
buy_stop_order(License_ID, symbol, lot, price)
Places a buy stop order above the current market price
Parameters:
License_ID (string) : Unique license ID of the user
symbol (string) : Trading symbol
lot (int) : Number of lots to buy
price (float) : Stop order price
Returns: String syntax for the buy stop order
sell_stop_order(License_ID, symbol, lot, price)
Places a sell stop order below the current market price
Parameters:
License_ID (string) : Unique license ID of the user
symbol (string) : Trading symbol
lot (int) : Number of lots to sell
price (float) : Stop order price
Returns: String syntax for the sell stop order
close_all_positions(License_ID, symbol)
Closes all positions for a specific symbol
Parameters:
License_ID (string) : Unique license ID of the user
symbol (string) : Trading symbol
Returns: String syntax for closing all positions
close_buy_positions(License_ID, symbol)
Closes all buy positions for a specific symbol
Parameters:
License_ID (string) : Unique license ID of the user
symbol (string) : Trading symbol
Returns: String syntax for closing all buy positions
close_sell_positions(License_ID, symbol)
Closes all sell positions for a specific symbol
Parameters:
License_ID (string) : Unique license ID of the user
symbol (string) : Trading symbol
Returns: String syntax for closing all sell positions
close_partial_buy_position(License_ID, symbol, lot)
Closes a partial buy position for a specific symbol
Parameters:
License_ID (string) : Unique license ID of the user
symbol (string) : Trading symbol
lot (int) : Number of lots to close
Returns: String syntax for closing a partial buy position
close_partial_sell_position(License_ID, symbol, lot)
Closes a partial sell position for a specific symbol
Parameters:
License_ID (string) : Unique license ID of the user
symbol (string) : Trading symbol
lot (int) : Number of lots to close
Returns: String syntax for closing a partial sell position
Request█ OVERVIEW
This library is a tool for Pine Script™ programmers that consolidates access to a wide range of lesser-known data feeds available on TradingView, including metrics from the FRED database, FINRA short sale volume, open interest, and COT data. The functions in this library simplify requests for these data feeds, making them easier to retrieve and use in custom scripts.
█ CONCEPTS
Federal Reserve Economic Data (FRED)
FRED (Federal Reserve Economic Data) is a comprehensive online database curated by the Federal Reserve Bank of St. Louis. It provides free access to extensive economic and financial data from U.S. and international sources. FRED includes numerous economic indicators such as GDP, inflation, employment, and interest rates. Additionally, it provides financial market data, regional statistics, and international metrics such as exchange rates and trade balances.
Sourced from reputable organizations, including U.S. government agencies, international institutions, and other public and private entities, FRED enables users to analyze over 825,000 time series, download their data in various formats, and integrate their information into analytical tools and programming workflows.
On TradingView, FRED data is available from ticker identifiers with the "FRED:" prefix. Users can search for FRED symbols in the "Symbol Search" window, and Pine scripts can retrieve data for these symbols via `request.*()` function calls.
FINRA Short Sale Volume
FINRA (the Financial Industry Regulatory Authority) is a non-governmental organization that supervises and regulates U.S. broker-dealers and securities professionals. Its primary aim is to protect investors and ensure integrity and transparency in financial markets.
FINRA's Short Sale Volume data provides detailed information about daily short-selling activity across U.S. equity markets. This data tracks the volume of short sales reported to FINRA's trade reporting facilities (TRFs), including shares sold on FINRA-regulated Alternative Trading Systems (ATSs) and over-the-counter (OTC) markets, offering transparent access to short-selling information not typically available from exchanges. This data helps market participants, researchers, and regulators monitor trends in short-selling and gain insights into bearish sentiment, hedging strategies, and potential market manipulation. Investors often use this data alongside other metrics to assess stock performance, liquidity, and overall trading activity.
It is important to note that FINRA's Short Sale Volume data does not consolidate short sale information from public exchanges and excludes trading activity that is not publicly disseminated.
TradingView provides ticker identifiers for requesting Short Sale Volume data with the format "FINRA:_SHORT_VOLUME", where "" is a supported U.S. equities symbol (e.g., "AAPL").
Open Interest (OI)
Open interest is a cornerstone indicator of market activity and sentiment in derivatives markets such as options or futures. In contrast to volume, which measures the number of contracts opened or closed within a period, OI measures the number of outstanding contracts that are not yet settled. This distinction makes OI a more robust indicator of how money flows through derivatives, offering meaningful insights into liquidity, market interest, and trends. Many traders and investors analyze OI alongside volume and price action to gain an enhanced perspective on market dynamics and reinforce trading decisions.
TradingView offers many ticker identifiers for requesting OI data with the format "_OI", where "" represents a derivative instrument's ticker ID (e.g., "COMEX:GC1!").
Commitment of Traders (COT)
Commitment of Traders data provides an informative weekly breakdown of the aggregate positions held by various market participants, including commercial hedgers, non-commercial speculators, and small traders, in the U.S. derivative markets. Tallied and managed by the Commodity Futures Trading Commission (CFTC) , these reports provide traders and analysts with detailed insight into an asset's open interest and help them assess the actions of various market players. COT data is valuable for gaining a deeper understanding of market dynamics, sentiment, trends, and liquidity, which helps traders develop informed trading strategies.
TradingView has numerous ticker identifiers that provide access to time series containing data for various COT metrics. To learn about COT ticker IDs and how they work, see our LibraryCOT publication.
█ USING THE LIBRARY
Common function characteristics
• This library's functions construct ticker IDs with valid formats based on their specified parameters, then use them as the `symbol` argument in request.security() to retrieve data from the specified context.
• Most of these functions automatically select the timeframe of a data request because the data feeds are not available for all timeframes.
• All the functions have two overloads. The first overload of each function uses values with the "simple" qualifier to define the requested context, meaning the context does not change after the first script execution. The second accepts "series" values, meaning it can request data from different contexts across executions.
• The `gaps` parameter in most of these functions specifies whether the returned data is `na` when a new value is unavailable for request. By default, its value is `false`, meaning the call returns the last retrieved data when no new data is available.
• The `repaint` parameter in applicable functions determines whether the request can fetch the latest unconfirmed values from a higher timeframe on realtime bars, which might repaint after the script restarts. If `false`, the function only returns confirmed higher-timeframe values to avoid repainting. The default value is `true`.
`fred()`
The `fred()` function retrieves the most recent value of a specified series from the Federal Reserve Economic Data (FRED) database. With this function, programmers can easily fetch macroeconomic indicators, such as GDP and unemployment rates, and use them directly in their scripts.
How it works
The function's `fredCode` parameter accepts a "string" representing the unique identifier of a specific FRED series. Examples include "GDP" for the "Gross Domestic Product" series and "UNRATE" for the "Unemployment Rate" series. Over 825,000 codes are available. To access codes for available series, search the FRED website .
The function adds the "FRED:" prefix to the specified `fredCode` to construct a valid FRED ticker ID (e.g., "FRED:GDP"), which it uses in request.security() to retrieve the series data.
Example Usage
This line of code requests the latest value from the Gross Domestic Product series and assigns the returned value to a `gdpValue` variable:
float gdpValue = fred("GDP")
`finraShortSaleVolume()`
The `finraShortSaleVolume()` function retrieves EOD data from a FINRA Short Sale Volume series. Programmers can call this function to retrieve short-selling information for equities listed on supported exchanges, namely NASDAQ, NYSE, and NYSE ARCA.
How it works
The `symbol` parameter determines which symbol's short sale volume information is retrieved by the function. If the value is na , the function requests short sale volume data for the chart's symbol. The argument can be the name of the symbol from a supported exchange (e.g., "AAPL") or a ticker ID with an exchange prefix ("NASDAQ:AAPL"). If the `symbol` contains an exchange prefix, it must be one of the following: "NASDAQ", "NYSE", "AMEX", or "BATS".
The function constructs a ticker ID in the format "FINRA:ticker_SHORT_VOLUME", where "ticker" is the symbol name without the exchange prefix (e.g., "AAPL"). It then uses the ticker ID in request.security() to retrieve the available data.
Example Usage
This line of code retrieves short sale volume for the chart's symbol and assigns the result to a `shortVolume` variable:
float shortVolume = finraShortSaleVolume(syminfo.tickerid)
This example requests short sale volume for the "NASDAQ:AAPL" symbol, irrespective of the current chart:
float shortVolume = finraShortSaleVolume("NASDAQ:AAPL")
`openInterestFutures()` and `openInterestCrypto()`
The `openInterestFutures()` function retrieves EOD open interest (OI) data for futures contracts. The `openInterestCrypto()` function provides more granular OI data for cryptocurrency contracts.
How they work
The `openInterestFutures()` function retrieves EOD closing OI information. Its design is focused primarily on retrieving OI data for futures, as only EOD OI data is available for these instruments. If the chart uses an intraday timeframe, the function requests data from the "1D" timeframe. Otherwise, it uses the chart's timeframe.
The `openInterestCrypto()` function retrieves opening, high, low, and closing OI data for a cryptocurrency contract on a specified timeframe. Unlike `openInterest()`, this function can also retrieve granular data from intraday timeframes.
Both functions contain a `symbol` parameter that determines the symbol for which the calls request OI data. The functions construct a valid OI ticker ID from the chosen symbol by appending "_OI" to the end (e.g., "CME:ES1!_OI").
The `openInterestFutures()` function requests and returns a two-element tuple containing the futures instrument's EOD closing OI and a "bool" condition indicating whether OI is rising.
The `openInterestCrypto()` function requests and returns a five-element tuple containing the cryptocurrency contract's opening, high, low, and closing OI, and a "bool" condition indicating whether OI is rising.
Example usage
This code line calls `openInterest()` to retrieve EOD OI and the OI rising condition for a futures symbol on the chart, assigning the values to two variables in a tuple:
= openInterestFutures(syminfo.tickerid)
This line retrieves the EOD OI data for "CME:ES1!", irrespective of the current chart's symbol:
= openInterestFutures("CME:ES1!")
This example uses `openInterestCrypto()` to retrieve OHLC OI data and the OI rising condition for a cryptocurrency contract on the chart, sampled at the chart's timeframe. It assigns the returned values to five variables in a tuple:
= openInterestCrypto(syminfo.tickerid, timeframe.period)
This call retrieves OI OHLC and rising information for "BINANCE:BTCUSDT.P" on the "1D" timeframe:
= openInterestCrypto("BINANCE:BTCUSDT.P", "1D")
`commitmentOfTraders()`
The `commitmentOfTraders()` function retrieves data from the Commitment of Traders (COT) reports published by the Commodity Futures Trading Commission (CFTC). This function significantly simplifies the COT request process, making it easier for programmers to access and utilize the available data.
How It Works
This function's parameters determine different parts of a valid ticker ID for retrieving COT data, offering a streamlined alternative to constructing complex COT ticker IDs manually. The `metricName`, `metricDirection`, and `includeOptions` parameters are required. They specify the name of the reported metric, the direction, and whether it includes information from options contracts.
The function also includes several optional parameters. The `CFTCCode` parameter allows programmers to request data for a specific report code. If unspecified, the function requests data based on the chart symbol's root prefix, base currency, or quoted currency, depending on the `mode` argument. The call can specify the report type ("Legacy", "Disaggregated", or "Financial") and metric type ("All", "Old", or "Other") with the `typeCOT` and `metricType` parameters.
Explore the CFTC website to find valid report codes for specific assets. To find detailed information about the metrics included in the reports and their meanings, see the CFTC's Explanatory Notes .
View the function's documentation below for detailed explanations of its parameters. For in-depth information about COT ticker IDs and more advanced functionality, refer to our previously published COT library .
Available metrics
Different COT report types provide different metrics . The tables below list all available metrics for each type and their applicable directions:
+------------------------------+------------------------+
| Legacy (COT) Metric Names | Directions |
+------------------------------+------------------------+
| Open Interest | No direction |
| Noncommercial Positions | Long, Short, Spreading |
| Commercial Positions | Long, Short |
| Total Reportable Positions | Long, Short |
| Nonreportable Positions | Long, Short |
| Traders Total | No direction |
| Traders Noncommercial | Long, Short, Spreading |
| Traders Commercial | Long, Short |
| Traders Total Reportable | Long, Short |
| Concentration Gross LT 4 TDR | Long, Short |
| Concentration Gross LT 8 TDR | Long, Short |
| Concentration Net LT 4 TDR | Long, Short |
| Concentration Net LT 8 TDR | Long, Short |
+------------------------------+------------------------+
+-----------------------------------+------------------------+
| Disaggregated (COT2) Metric Names | Directions |
+-----------------------------------+------------------------+
| Open Interest | No Direction |
| Producer Merchant Positions | Long, Short |
| Swap Positions | Long, Short, Spreading |
| Managed Money Positions | Long, Short, Spreading |
| Other Reportable Positions | Long, Short, Spreading |
| Total Reportable Positions | Long, Short |
| Nonreportable Positions | Long, Short |
| Traders Total | No Direction |
| Traders Producer Merchant | Long, Short |
| Traders Swap | Long, Short, Spreading |
| Traders Managed Money | Long, Short, Spreading |
| Traders Other Reportable | Long, Short, Spreading |
| Traders Total Reportable | Long, Short |
| Concentration Gross LE 4 TDR | Long, Short |
| Concentration Gross LE 8 TDR | Long, Short |
| Concentration Net LE 4 TDR | Long, Short |
| Concentration Net LE 8 TDR | Long, Short |
+-----------------------------------+------------------------+
+-------------------------------+------------------------+
| Financial (COT3) Metric Names | Directions |
+-------------------------------+------------------------+
| Open Interest | No Direction |
| Dealer Positions | Long, Short, Spreading |
| Asset Manager Positions | Long, Short, Spreading |
| Leveraged Funds Positions | Long, Short, Spreading |
| Other Reportable Positions | Long, Short, Spreading |
| Total Reportable Positions | Long, Short |
| Nonreportable Positions | Long, Short |
| Traders Total | No Direction |
| Traders Dealer | Long, Short, Spreading |
| Traders Asset Manager | Long, Short, Spreading |
| Traders Leveraged Funds | Long, Short, Spreading |
| Traders Other Reportable | Long, Short, Spreading |
| Traders Total Reportable | Long, Short |
| Concentration Gross LE 4 TDR | Long, Short |
| Concentration Gross LE 8 TDR | Long, Short |
| Concentration Net LE 4 TDR | Long, Short |
| Concentration Net LE 8 TDR | Long, Short |
+-------------------------------+------------------------+
Example usage
This code line retrieves "Noncommercial Positions (Long)" data, without options information, from the "Legacy" report for the chart symbol's root, base currency, or quote currency:
float nonCommercialLong = commitmentOfTraders("Noncommercial Positions", "Long", false)
This example retrieves "Managed Money Positions (Short)" data, with options included, from the "Disaggregated" report:
float disaggregatedData = commitmentOfTraders("Managed Money Positions", "Short", true, "", "Disaggregated")
█ NOTES
• This library uses dynamic requests , allowing dynamic ("series") arguments for the parameters defining the context (ticker ID, timeframe, etc.) of a `request.*()` function call. With this feature, a single `request.*()` call instance can flexibly retrieve data from different feeds across historical executions. Additionally, scripts can use such calls in the local scopes of loops, conditional structures, and even exported library functions, as demonstrated in this script. All scripts coded in Pine Script™ v6 have dynamic requests enabled by default. To learn more about the behaviors and limitations of this feature, see the Dynamic requests section of the Pine Script™ User Manual.
• The library's example code offers a simple demonstration of the exported functions. The script retrieves available data using the function specified by the "Series type" input. The code requests a FRED series or COT (Legacy), FINRA Short Sale Volume, or Open Interest series for the chart's symbol with specific parameters, then plots the retrieved data as a step-line with diamond markers.
Look first. Then leap.
█ EXPORTED FUNCTIONS
This library exports the following functions:
fred(fredCode, gaps)
Requests a value from a specified Federal Reserve Economic Data (FRED) series. FRED is a comprehensive source that hosts numerous U.S. economic datasets. To explore available FRED datasets and codes, search for specific categories or keywords at fred.stlouisfed.org Calls to this function count toward a script's `request.*()` call limit.
Parameters:
fredCode (series string) : The unique identifier of the FRED series. The function uses the value to create a valid ticker ID for retrieving FRED data in the format `"FRED:fredCode"`. For example, `"GDP"` refers to the "Gross Domestic Product" series ("FRED:GDP"), and `"GFDEBTN"` refers to the "Federal Debt: Total Public Debt" series ("FRED:GFDEBTN").
gaps (simple bool) : Optional. If `true`, the function returns a non-na value only when a new value is available from the requested context. If `false`, the function returns the latest retrieved value when new data is unavailable. The default is `false`.
Returns: (float) The value from the requested FRED series.
finraShortSaleVolume(symbol, gaps, repaint)
Requests FINRA daily short sale volume data for a specified symbol from one of the following exchanges: NASDAQ, NYSE, NYSE ARCA. If the chart uses an intraday timeframe, the function requests data from the "1D" timeframe. Otherwise, it uses the chart's timeframe. Calls to this function count toward a script's `request.*()` call limit.
Parameters:
symbol (series string) : The symbol for which to request short sale volume data. If the specified value contains an exchange prefix, it must be one of the following: "NASDAQ", "NYSE", "AMEX", "BATS".
gaps (simple bool) : Optional. If `true`, the function returns a non-na value only when a new value is available from the requested context. If `false`, the function returns the latest retrieved value when new data is unavailable. The default is `false`.
repaint (simple bool) : Optional. If `true` and the chart's timeframe is intraday, the value requested on realtime bars may change its time offset after the script restarts its executions. If `false`, the function returns the last confirmed period's values to avoid repainting. The default is `true`.
Returns: (float) The short sale volume for the specified symbol or the chart's symbol.
openInterestFutures(symbol, gaps, repaint)
Requests EOD open interest (OI) and OI rising information for a valid futures symbol. If the chart uses an intraday timeframe, the function requests data from the "1D" timeframe. Otherwise, it uses the chart's timeframe. Calls to this function count toward a script's `request.*()` call limit.
Parameters:
symbol (series string) : The symbol for which to request open interest data.
gaps (simple bool) : Optional. If `true`, the function returns non-na values only when new values are available from the requested context. If `false`, the function returns the latest retrieved values when new data is unavailable. The default is `false`.
repaint (simple bool) : Optional. If `true` and the chart's timeframe is intraday, the value requested on realtime bars may change its time offset after the script restarts its executions. If `false`, the function returns the last confirmed period's values to avoid repainting. The default is `true`.
Returns: ( ) A tuple containing the following values:
- The closing OI value for the symbol.
- `true` if the closing OI is above the previous period's value, `false` otherwise.
openInterestCrypto(symbol, timeframe, gaps, repaint)
Requests opening, high, low, and closing open interest (OI) data and OI rising information for a valid cryptocurrency contract on a specified timeframe. Calls to this function count toward a script's `request.*()` call limit.
Parameters:
symbol (series string) : The symbol for which to request open interest data.
timeframe (series string) : The timeframe of the data request. If the timeframe is lower than the chart's timeframe, it causes a runtime error.
gaps (simple bool) : Optional. If `true`, the function returns non-na values only when new values are available from the requested context. If `false`, the function returns the latest retrieved values when new data is unavailable. The default is `false`.
repaint (simple bool) : Optional. If `true` and the `timeframe` represents a higher timeframe, the function returns unconfirmed values from the timeframe on realtime bars, which repaint when the script restarts its executions. If `false`, it returns only confirmed higher-timeframe values to avoid repainting. The default is `true`.
Returns: ( ) A tuple containing the following values:
- The opening, high, low, and closing OI values for the symbol, respectively.
- `true` if the closing OI is above the previous period's value, `false` otherwise.
commitmentOfTraders(metricName, metricDirection, includeOptions, CFTCCode, typeCOT, mode, metricType)
Requests Commitment of Traders (COT) data with specified parameters. This function provides a simplified way to access CFTC COT data available on TradingView. Calls to this function count toward a script's `request.*()` call limit. For more advanced tools and detailed information about COT data, see TradingView's LibraryCOT library.
Parameters:
metricName (series string) : One of the valid metric names listed in the library's documentation and source code.
metricDirection (series string) : Metric direction. Possible values are: "Long", "Short", "Spreading", and "No direction". Consult the library's documentation or code to see which direction values apply to the specified metric.
includeOptions (series bool) : If `true`, the COT symbol includes options information. Otherwise, it does not.
CFTCCode (series string) : Optional. The CFTC code for the asset. For example, wheat futures (root "ZW") have the code "001602". If one is not specified, the function will attempt to get a valid code for the chart symbol's root, base currency, or main currency.
typeCOT (series string) : Optional. The type of report to request. Possible values are: "Legacy", "Disaggregated", "Financial". The default is "Legacy".
mode (series string) : Optional. Specifies the information the function extracts from a symbol. Possible modes are:
- "Root": The function extracts the futures symbol's root prefix information (e.g., "ES" for "ESH2020").
- "Base currency": The function extracts the first currency from a currency pair (e.g., "EUR" for "EURUSD").
- "Currency": The function extracts the currency of the symbol's quoted values (e.g., "JPY" for "TSE:9984" or "USDJPY").
- "Auto": The function tries the first three modes (Root -> Base currency -> Currency) until it finds a match.
The default is "Auto". If the specified mode is not available for the symbol, it causes a runtime error.
metricType (series string) : Optional. The metric type. Possible values are: "All", "Old", "Other". The default is "All".
Returns: (float) The specified Commitment of Traders data series. If no data is available, it causes a runtime error.
PremiumDiscountLibraryLibrary "PremiumDiscountLibrary"
isInZone(currentTime, price, trend, tz)
Vérifie si le prix est en zone premium ou discount
Parameters:
currentTime (int) : L'heure actuelle (timestamp)
price (float) : Le prix actuel
trend (string) : La tendance ("bullish" ou "bearish")
tz (string) : Le fuseau horaire pour calculer les sessions (par défaut : "GMT+1")
Returns: true si le prix est dans la zone correcte, sinon false
KillzoneLibraryLibrary "KillzoneLibrary"
isKillzone(currentTime, tz)
Vérifie si l'heure actuelle est dans une Killzone
Parameters:
currentTime (int) : L'heure actuelle (entier représentant le timestamp)
tz (string) : Le fuseau horaire (par défaut : "GMT+1")
Returns: true si dans une Killzone, sinon false